Cancer diagnosis and treatment decisions have historically been based on anatomic sites of origin and spread; however, the emerging paradigm incorporates key genetic attributes of a given tumor to predict clinical behavior and specify the optimal use of targeted therapeutics. Ultimately, the delivery of personalized cancer medicine will require systematic characterization of all therapeutically informative tumor genomic alterations in the clinical and translational arena. Previously, we developed and deployed OncoMap, a mass spectrometric genotyping-based platform that enables high-throughput profiling of hundreds of known mutations across dozens of cancer genes. This platform performs well and has launched a robust translational oncology effort. However, the mass spectrometric genotyping technology remains limited in scope, assay sensitivity, and the type of genomic alteration that can be identified. Recently, it has become possible to render multi-faceted tumor characterization both technologically feasible and economically accessible through massively parallel sequencing (MPS) technology. Thus, the goal of this application is to migrate the OncoMap approach to an MPS platform (Illumina), empowered by innovations such as solution-phase exon capture and sample barcoding. Together with our colleagues at the Dana-Farber Cancer Institute and Broad Institute, we have generated preliminary data showing the feasibility and promise of each of these components, thereby raising the possibility of comprehensive tumor sequencing at a low per-sample cost. Accordingly, in this R33 application we will implement a transformative platform for systematic tumor genomic profiling, which we call MPS-OncoMap. To accomplish this we will optimize the methodology for sample barcoding technology, solution-phase exon capture, and single-molecule sequencing to enable robust mutation profiling (base mutations, amplifications, and deletions) across ~150 cancer genes in at least 12 tumor samples simultaneously. We will test the performance of MPS-OncoMap using DNA from cancer cell lines, frozen tumors, and formalin-fixed, paraffin-embedded tumor tissue for which the ground truth is known for multiple genetic alterations. Finally, we will implement MPS-OncoMap at production scale to enable systematic analyses for many translational oncology applications. Achieving these Aims may inform a definitive path to comprehensive tumor genomic profiling with far-reaching impact in the translational and clinical oncology arena.